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Record W7133078898

Perceptions of the West by Chinese International Graduate Students before and after Arriving in Canada

2022· dissertation· W7133078898 on OpenAlexaboutno aff
Mingyi Li

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsChinaAutonomyPerceptionRacismPandemicRace (biology)Institutional racism
DOInot available

Abstract

fetched live from OpenAlex

It is evident that China has undergone significant changes over the past few decades because of its reform and opening door policy since the late 1970s. Chinese citizens born in the 1990s grew up in an era of significant historical change. This study examined how has western influence affected the 1990s generation of Chinese students’ understanding of the West before they came to Canada, and how have participants’ understandings about the West been changed by their learning and living experiences in Canada.The findings of this study suggest that participants were unaware of their racialized location when settling in Canada due to the lack of critical discourses of race in their home country. It also reveals that the racism against Chinese students during the Covid-19 pandemic have forced participants to re-evaluate their career trajectories. Another significant finding was that not all Chinese/Asian parents expected their children to be the top student in school as common stereotypes have illustrated; rather, the parents of the selected participants sent and supported their children to study in western countries because they wished their children to have more opportunities and more autonomy in terms of their own career and passions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.006
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.362
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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